- Collected the data and organized it to form a meaningful dataset.
- Checked for null values and took care of it.
- Observed the data to form meaningful insights!
- Did Exploratory Data Analysis on the dataset.
- Used correlations to form a heatmap.
- Visualizations were made by using Matplotlib and Seaborn Libraries..
- Did Data Preprocessing.
- Used One-Hot Encoding for conversion of categorical data to Numerical data.
- Did Train-Test split
- Fitted the model.
- predicted the test scores.
- Plotted the prediction.
Prediction plot gave a Normal Distribution curve.
- Plotted the Best fit line for the model...
- Calculated Mean Absolute error and Root Mean Squared Error!
- Fitted the model.
- predicted the test scores.
- Plotted the prediction.
Prediction plot gave a slightly better Normal Distribution curve than that of Random Forest.
- Plotted the Best fit line for the model.!!
- Calculated Mean Absolute error and Root Mean Squared Error.